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Automatic body measurement based on slicing loops

Yueqi Zhong (College of Textiles, Donghua University, Shanghai, China) (Key Lab of Textile Science and Technology, Donghua University, Shanghai, China)
Duan Li (College of Textiles, Donghua University, Shanghai, China)
Ge Wu (College of Textiles, Donghua University, Shanghai, China)
PengPeng Hu (College of Textiles, Donghua University, Shanghai, China)

International Journal of Clothing Science and Technology

ISSN: 0955-6222

Article publication date: 30 April 2018

Issue publication date: 24 July 2018

174

Abstract

Purpose

The automatic body measurement is the key of tailoring, mass customization and fit/ease evaluation. The major challenges include finding the landmarks and extracting the sizes accurately. The purpose of this paper is to propose a new method of body measurement based on the loop structure.

Design/methodology/approach

The scanned human model is sliced equally to layers consist of various shapes of loops. The semantic feature analysis has been regarded as a problem of finding the points of interest (POI) and the loop of interest (LOI) according to the types of loop connections. Methods for determining the basic landmarks have been detailed.

Findings

The experimental results validate that the proposed methods can be used to locate the landmarks and to extract sizes on markless human scans robustly and efficiently.

Originality/value

With the method, the body measurement can be quickly performed with average errors around 0.5 cm. The results of segmentation, landmarking and body measurements also validate the robustness and efficiency of the proposed methods.

Keywords

Acknowledgements

This work was supported by Natural Science Foundation of China (61572124).

Citation

Zhong, Y., Li, D., Wu, G. and Hu, P. (2018), "Automatic body measurement based on slicing loops", International Journal of Clothing Science and Technology, Vol. 30 No. 3, pp. 380-397. https://doi.org/10.1108/IJCST-06-2017-0086

Publisher

:

Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

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